Data-Driven Kinematic Model of PneuNets Bending Actuators for Soft Grasping Tasks

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

BACKGROUND

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke.

METHODS

The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires.

RESULTS

Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported.

CONCLUSIONS

Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.

Mathematical Modeling of a Multi-Chamber Pneumatic Soft Actuator

Owing to their compliance with most shapes, soft actuators are regarded as cost-effective solutions for grasping irregular objects. The material properties of nonlinear elastic polymers are considered necessary for the correct implementation of these actuators. The analysis tends to be complex even for simple movements defined by theoretically infinite degrees of freedom. This study offers a mathematical model that outlines a relationship between the energy provided by a pressure source and the expected behavior of multi-chamber pneumatic soft actuators through hyper-elastic material deformation interpretation, geometric approximations, and the vectorial representations of their segments. Digitally analyzed empirical results measured through lateral pictures of an actuator were taken at different pressure references. Direct comparisons between the average value of the tested angles and those calculated through the tuned mathematical model provide a maximum error of 0.647° for small deformations and an improved accuracy at higher pressure inputs. This study offers a valid tool applicable to the design of soft actuators and their further analysis without the need for overly complex methods.